## ----setup, include=FALSE------------------------------------------------
opts_chunk$set(cache=TRUE)


## ----, eval=FALSE--------------------------------------------------------
## library(LeviRmisc)
## df <- geoPmidLookup(c("GSE26712", "PMID18593951"))


## ------------------------------------------------------------------------
library(curatedOvarianData)
data(package="curatedOvarianData")


## ------------------------------------------------------------------------
download.file("https://bitbucket.org/lwaldron/ovrc4_sigvalidation/raw/tip/input/patientselection.config", method="wget", destfile="patientselection.config")
source("patientselection.config")
impute.missing <- TRUE
keep.common.only <- TRUE


## ----, results="hide"----------------------------------------------------
download.file("https://bitbucket.org/lwaldron/ovrc4_sigvalidation/raw/tip/src/createEsetList_source.R", method="wget", destfile="createEsetList.R")
source("createEsetList.R")


## ------------------------------------------------------------------------
length(esets)


## ------------------------------------------------------------------------
runCox <- function(eset, probeset="CXCL12"){
  library(survival)
  eset$y <- Surv(eset$days_to_death, eset$vital_status == "deceased")
  if(probeset %in% featureNames(eset)){
    obj <- coxph(eset$y ~ scale(t(exprs(eset[probeset, ]))[, 1]))
    output <- c(obj$coefficients, sqrt(obj$var))
    names(output) <- c("log.HR", "SE")
  }else{output <- NULL}
    output}
runCox(esets[[1]])


## ------------------------------------------------------------------------
study.coefs <- t(sapply(esets, runCox)); head(study.coefs)


## ----, height=5----------------------------------------------------------
library(metafor)
res.fe <- metafor::rma(yi=study.coefs[, 1], sei=study.coefs[, 2], method="FE")
forest.rma(res.fe, slab=gsub("_eset$","",rownames(study.coefs)), atransf=exp)


## ------------------------------------------------------------------------
(res.re <- metafor::rma(yi=study.coefs[, 1], sei=study.coefs[, 2], method="DL"))


## ----, eval=TRUE---------------------------------------------------------
if( !require("survHD") || package.version("survHD") != "0.5.0" ){
    library(devtools)
    install_url("https://bitbucket.org/lwaldron/survhd/downloads/survHD_0.5.0.tar.gz")
}
download.file("https://bitbucket.org/lima1/ovrc4_signew/raw/tip/src/metaCMA.R", destfile="metaCMA.R", method="wget")
source("metaCMA.R")
gene.coefs <- metaCMA.coefs(esets)
FE.res <- metaCMA.opt(esets=esets, coefs=gene.coefs, rma.method="FE", n=200)


## ----, eval=TRUE---------------------------------------------------------
LODO.res <- metaCMA(esets,coefs=gene.coefs,n=200, rma.method="FE")